Stavros N. Moutsis
Papers
1
Total Citations
11
H-Index
1
About
Stavros N. Moutsis is a researcher at the forefront of embedded computer vision and human-action recognition, with a focused interest in developing efficient, real-time safety systems. His most cited work, "Fall detection paradigm for embedded devices based on YOLOv8" (2023, 11 citations), addresses a critical global health challenge: the 37.3 million fall-related accidents occurring annually. By adapting the state-of-the-art YOLOv8 object detection model for resource-constrained hardware, Moutsis demonstrates a key contribution—bridging the gap between high-accuracy deep learning and practical, deployable edge computing. This paradigm is particularly vital for elderly care, where immediate, on-device detection can drastically reduce response times. His research not only advances the technical field of action recognition but also directly tackles a pressing societal need, showcasing a commitment to impactful, applied AI. Moutsis’s work stands as a notable achievement in making sophisticated computer vision accessible for life-saving applications, positioning him as a promising voice in the intersection of embedded systems and assistive technology.
Research Focus
Key Achievements
Top Papers
- 1Fall detection paradigm for embedded devices based on YOLOv811 citations · 2023